Classical Type-1 Research Articles

Interpolation functions of interval type-2 fuzzy systems

The interpolation functions of interval type-2 fuzzy systems and their universal approximation are investigated in this paper. Two types of fuzzification methods are designed to construct the antecedents and consequents of the type-2 inference rules. Then the properties of the fuzzy operator and the type-reduction algorithm are used to integrate all parts of the fuzzy system. Interpolation functions of interval type-2 fuzzy systems, which are proved to be universal approximators, are obtained based on three models, namely single input and single output, double inputs and single output, and multiple inputs and single output. The proposed approach is applied to approximate experiments of dynamic systems so as to evaluate the system performance. The system parameters are optimized by the QPSO algorithm. Experimental results for several data sets are given to show the approximation performances of the proposed interpolation functions are better than those of the interpolation function of the classical type-1 fuzzy system.

Resilience-Based Efficiency Measurement of Process Industries with Type-2 Fuzzy Sets

Today’s business environments are prone to high levels of uncertainties and risks because the speed of changes is too high. Hence, the way of dealing with threats has changed. Complex socio-technical systems (CSSs) are confronted with out-of-control disturbances that need risk management systems to be applied. Risk management is organized activities to monitor and control risks in CSSs. Newly, resilience engineering (RE) as a safety management discipline has been expanded to change the attitude to risks. RE is defined as the capability of a system to absorb disturbances and adapt to rapidly changing conditions. Process industries as CSS, are potentially disposed to catastrophic events such as explosions, toxic leakages, stoppages of production operations, etc. In this paper, a novel RE-based algorithm is developed to measure the efficiency of process industries for preventing and reducing disorders considering their high-level of uncertainty. To do this, firstly, resilience indices in an oil refinery as an essential process industry are extracted. Then, using type-2 fuzzy data envelopment analysis (DEA), a new multi-objective approach is presented to evaluate the efficiency of DMUs from the perspective of RE. Interval type-2 fuzzy sets (IT2 FSs) is used in this approach because they potentially hold more implication than the classical type-1 fuzzy sets (T1 FSs). As a case study, a refinery as a CSS is evaluated. Using the proposed algorithm shows the efficiency scores of DMUs in the refinery. By conducting a comparative analysis, it was revealed that the proposed model outperforms classical methods. The results of the proposed approach show that besides simplicity, there is good stability to consider the criteria of RE in efficiency measurement with IT2 FSs.

On the influence of using fuzzy extensions in linguistic fuzzy rule-based regression systems

Fuzzy Rule-Based Systems, FRBSs, are powerful tools to address regression problems. They can model the relationship between inputs and outputs by linguistic concepts. However, those FRBSs which are based on the conventional Type-1 fuzzy sets may not be able to handle some difficulties of real-world applications. In such situations, using novel representations of fuzzy sets seems like a good idea. Different extensions of fuzzy sets usually help to provide more precise models in the real-world problems. In this study, the influence of using fuzzy extensions in improving the efficiency of linguistic fuzzy rule-based regression models is investigated. For this purpose, a conventional Type-1 Mamdani FRBS is adapted to the three extensions of fuzzy sets, namely Interval Type-2, Intuitionistic, and Interval Type-2 Intuitionistic fuzzy sets. A two-pass method is proposed to define membership (non-membership) functions of these fuzzy sets; this method is based on the 3-tuples representation of the standard Type-1 membership functions. Wang and Mendel’s rule learning method is adapted to extract fuzzy rules from regression data. In order to tune the membership functions up to different extents, three evolutionary extensions are also presented for each type of the proposed FRBSs. Individual, internal, and external comparisons of the proposed FRBSs were done using 22 real-world regression datasets and statistical tests. Experimental results confirm that all the three proposed FRBSs outperform the classical Type-1 framework; furthermore, the Interval Type-2 Intuitionistic FRBS is the superior system so that an appropriate tuning of its parameters makes it the most accurate model.

Interval Type-2 A-Intuitionistic Fuzzy Logic for Regression Problems

This paper presents an approach to prediction based on a new interval type-2 Atanassov-intuitionistic fuzzy logic system (IT2AIFLS) of the Takagi–Sugeno–Kang fuzzy inference with neural network learning capability. The gradient descent algorithm is used to adapt the parameters of the IT2AIFLS. The empirical comparison is made on the designed system using some benchmark regression problems—both artificial and real-world datasets. Analyses of our results reveal that IT2AIFLS outperforms its type-1 variant, other type-1 fuzzy logic approaches, and some type-2 fuzzy systems in the regression tasks. The reason for the improved performance of the proposed framework of IT2AIFLS is the introduction of nonmembership functions and intuitionistic fuzzy indices into the classical IT2FLS model. This increases the level of fuzziness in the proposed IT2AIFLS framework, thus providing more accurate approximations than AIFLS, classical type-1, and interval type-2 fuzzy logic systems.

Type-2 Fuzzy Curve Model

The paper discusses about the formulation of type-2 fuzzy curve model. The generalization is carried out due to the existence of complex uncertainty which cannot be represented with classical type-1 fuzzy set. Hence, type-2 fuzzy set is proposed to define this type of complex uncertainty. Based on the complex uncertainty of data, fuzzy set theory type-2 with fuzzy number type-2 concept is used to represent the data with complex uncertainty. This process re-defines the data as type-2 fuzzy data which is also the result obtained by generalizing type-1 fuzzy data. Therefore, B-spline function is chosen to show the development of type-2 B-spline curve model via generalization. It is then followed by a number of processes, i.e. fuzzification, reduction and defuzzification are defined to model type-2 fuzzy B-spline curve to obtain a crisp type-2 fuzzy curve.

Murine CD103+ dendritic cells protect against steatosis progression towards steatohepatitis

Non-alcoholic fatty liver (NAFL) is the hepatic consequence of metabolic syndrome and can progress to non-alcoholic steatohepatitis (NASH). The identification of molecular and cellular factors that determine the progression of NASH and lead to irreversible hepatocellular damage are crucial. Dendritic cells (DCs) represent a heterogeneous cell population among which CD103+ DCs play a significant role in immunity and tolerance. We aimed to clarify the role of this DC subset in the pathomechanism of NASH. Steatosis progression towards steatohepatitis was analysed using multicolor FACS analyses, cytokine and qPCR array in high sucrose diet (HSD) and methionine and choline deficient diet (MCD) fed wild-type and basic leucine zipper transcription factor, ATF-Like-3 (Batf3) deficient animals, which lack CD103+ DCs (classical type-1 DC, cDC1s). Metabolic challenge of Batf3-/- animals resulted in the progression of steatosis towards steatohepatitis, manifesting by an increased influx of inflammatory cells into the liver and elevated inflammatory cytokine production of myeloid cells upon innate stimuli. However, the lack of cDC1s did not affect cellular apoptosis and fibrosis progression but altered genes involved in lipid metabolism. The adoptive transfer of CD103+ cDC1s to Batf3 deficient animals reversed these observed changes and more importantly could attenuate cellular damage and inflammation in established murine steatohepatitis. Here, we have identified the murine CD103+ cDC1s as a protective DC subtype that influences the pro-anti-inflammatory balance and protects the liver from metabolic damage. As guardians of liver integrity, they play a key role in the inflammatory process during the development of steatohepatitis in mice. Non-alcoholic fatty liver (NAFL) is the hepatic consequence of metabolic syndrome and can lead to non-alcoholic steatohepatitis (NASH). The current study demonstrated that a specific murine dendritic cell subtype possesses a potent regulatory role to influence the inflammatory milieu of the liver in this process.

Bypassing the Natural Visual-Motor Pathway to Execute Complex Movement Related Tasks Using Interval Type-2 Fuzzy Sets.

In visual-motor coordination, the human brain processes visual stimuli representative of complex motion-related tasks at the occipital lobe to generate the necessary neuronal signals for the parietal and pre-frontal lobes, which in turn generates movement related plans to excite the motor cortex to execute the actual tasks. The paper introduces a novel approach to provide rehabilitative support to patients suffering from neurological damage in their pre-frontal, parietal and/or motor cortex regions. An attempt to bypass the natural visual-motor pathway is undertaken using interval type-2 fuzzy sets to generate the approximate EEG response of the damaged pre-frontal/parietal/motor cortex from the occipital EEG signals. The approximate EEG response is used to trigger a pre-trained joint coordinate generator to obtain the desired joint coordinates of the link end-points of a robot imitating the human subject. The robot arm is here employed as a rehabilitative aid in order to move each link end-points to the desired locations in the reference coordinate system by appropriately activating its links using the well-known inverse kinematics approach. The mean-square positional errors obtained for each link end-points is found within acceptable limits for all experimental subjects including subjects with partial parietal damage, indicating a possible impact of the proposed approach in rehabilitative robotics. Subjective variation in EEG features over different sessions of experimental trials is modeled here using interval type-2 fuzzy sets for its inherent power to handle uncertainty. Experiments undertaken confirm that interval type-2 fuzzy realization outperforms its classical type-1 counterpart and back-propagation neural approaches in all experimental cases, considering link positional error as a metric. The proposed research offers a new opening for the development of possible rehabilitative aids for people with partial impairment in visual-motor coordination.

Interval Type-2 Fuzzy Logic System for Dynamic Spectrum Access in Cognitive Radio

current scenario has shown that, with the conventional spectrum access approach, the radio spectrum allocated to primary (licensed) users is hugely underutilized. While many spectrum methods have been proposed to utilize spectrum efficient manner, the spectrum access opportunistic way is happen to the most practical approach to attain near-optimal spectrum utilization by permitting secondary (unlicensed) users to sense and access available spectrum opportunistically. In this paper, we present decision making scheme in cognitive radio based on Interval type-2 fuzzy logic system. Here, classical type-1 and Interval type-2 fuzzy logic system has been compared in terms of possibility of spectrum access by the secondary user with effective and seamless communication between cognitive radio and primary user. The proposed fuzzy inference system has three input parameters such as spectrum utilization efficiency, degree of mobility and distance to primary user of cognitive radio, along with output parameter as the possibility of accessing the spectrum for secondary user based on linguistic knowledge of 27 rules. This paper mainly deals with design of decision making scheme using Interval type-2 fuzzy logic for minimizing the effect of uncertainty produced by the measurement and environmental noise. Simulation result shows significant enhancement in dynamic spectrum allocation for secondary user with higher probability conditions. KeywordsRadio, Type-1 fuzzy logic, Interval Type-2 Fuzzy

Terlipressin and albumin for type-1 hepatorenal syndrome associated with sepsis

Terlipressin and albumin is the standard of care for classical type-1 hepatorenal syndrome (HRS) not associated with active infections. However, there is no information on efficacy and safety of this treatment in patients with type-1 HRS associated with sepsis. Study aim was to investigate the effects of early treatment with terlipressin and albumin on circulatory and kidney function in patients with type-1 HRS and sepsis and assess factors predictive of response to therapy. Prospective study in 18 consecutive patients with type-1 HRS associated with sepsis. Treatment was associated with marked improvement in arterial pressure and suppression of the high levels of plasma renin activity and norepinephrine. Response to therapy (serum creatinine <1.5mg/dl) was achieved in 12/18 patients (67%) and was associated with improved 3-month survival compared to patients without response. Non-responders had significantly lower baseline heart rate, poor liver function tests, slightly higher serum creatinine, and higher Child-Pugh and MELD scores compared to responders. Interestingly, non-responders had higher values of CLIF-SOFA score compared to responders (14±3 vs. 8±1, respectively p<0.001), indicating greater severity of acute-on-chronic liver failure (ACLF). A CLIF-SOFA score ⩾11 had 92% sensitivity and 100% specificity in predicting no response to therapy. No significant differences were observed between responders and non-responders in baseline urinary kidney biomarkers. Treatment was safe and no patient required withdrawal of terlipressin. Early treatment with terlipressin and albumin in patients with type-1 HRS associated with sepsis is effective and safe. Patients with associated severe ACLF are unlikely to respond to treatment.

Urinary neutrophil gelatinase-associated lipocalin as biomarker in the differential diagnosis of impairment of kidney function in cirrhosis

Impairment of kidney function is common in cirrhosis but differential diagnosis remains a challenge. We aimed at assessing the usefulness of neutrophil gelatinase-associated lipocalin (NGAL), a biomarker of tubular damage, in the differential diagnosis of impairment of kidney function in cirrhosis. Two-hundred and forty-one patients with cirrhosis, 72 without ascites, 85 with ascites, and 84 with impaired kidney function, were studied. Urinary levels of NGAL were measured by ELISA. Patients with impaired kidney function had higher urinary NGAL levels compared to patients with and without ascites. Patients with urinary tract infection (n=25) had higher uNGAL values than non-infected patients. Patients with acute tubular necrosis (ATN) had uNGAL levels markedly higher (417μg/g creatinine (239-2242) median and IQ range) compared to those of patients with pre-renal azotemia due to volume depletion 30 (20-59), chronic kidney disease (CKD) 82 (34-152), and hepatorenal syndrome (HRS) 76 (43-263) μg/g creatinine (p<0.001 for all). Among HRS patients, the highest values were found in HRS-associated with infections, followed by classical (non-associated with active infections) type-1 and type-2 HRS (391 (72-523), 147 (83-263), and 43 (31-74) μg/g creatinine, respectively; p<0.001). Differences in uNGAL levels between classical type 1 HRS and ATN on the one hand and classical type 1 HRS and CKD and pre-renal azotemia on the other were statistically significant (p<0.05). uNGAL levels may be useful in the differential diagnosis of impairment of kidney function in cirrhosis. Urinary tract infections should be ruled out because they may increase uNGAL excretion.

Nuocytes: expanding the innate cell repertoire in type-2 immunity

Activation and differentiation of the Th1 cell population lead to their production of the classical type-1 cytokines IFN-γ, IL-2, and TNF-β, thus promoting type-1 immunity. This is thought to occur via the ligation of TLRs by bacterial and viral products, which in turn, drive production of the essential Th1 cell differentiation factor, IL-12, by dendritic cells (DCs). Concurrent studies have been able to identify the effector cytokines produced by Th2 cells (IL-4, IL-5, IL-9, and IL-13) as being essential for parasitic immunity and also as essential factors in allergic asthma. However, the factors that are critical for initiation of the type-2 response remained obscure. Recently however, two critical observations have led to a more detailed understanding of the innate type-2 response. First, two novel, type-2-inducing cytokines-IL-25 and IL-33-were identified as being necessary for the up-regulation of the type-2 effector cytokines, mirroring the role of IL-12 in the type-1 response. Second, studies focused on target cell populations of IL-25 and IL-33 have identified novel, innate cell populations, which potentially bridge the gap between presentation of the type-2-inducing cytokine and the later adaptive Th2 cell response. In this review, we will discuss these new type-2 innate cell populations, in particular, the recently discovered nuocyte population, which are required for type-2 responses against helminthic parasites.

Sequence-Based Discovery of the Human and Rodent Peroxisomal Proteome

Peroxisomes are metabolic organelles present in virtually all eukaryotic cells. They contain enzymes involved in hydrogen peroxide-based respiration and lipid metabolism. At present, only a small number of peroxisomal enzymes that are associated with oxidative stress response and metabolic disorders have been characterised biochemically. Therefore, we devised a sequence-based, multistep knowledge discovery strategy to identify potential novel peroxisomal protein candidates in small rodent model organisms and human. Screening of 130,629 putative translations of GenBank rodent and primate mRNA sequences was limited to the classical type-1 peroxisomal targeting signal [SA]-K-L. This motif is over-represented among peroxisomal proteins and has a high targeting efficiency. Subsequent steps of identifying co-occurring motifs, secondary structure properties, orthologues and variants, in combination with literature searching and visual inspection by domain experts, aimed at reduction of both false positive and negative validation targets. Our method yielded 117 known peroxisome-targeted proteins and 29 novel candidate proteins. Of special interest were the mouse C530046K17Rik and 1300019N10Rik protein sequences that contain domains associated with enzymatic functions. C530046K17Rik showed no similarity to any known sequence of the animal kingdom, but weak similarity to the possible Leishmania quinone oxidoreductase and a putative cyanobacterium nicotinamide adenine dinucleotide phosphate (NADP)-dependent oxidoreductase. 1300019N10Rik contains two protease-related domains, glutamyl endopeptidase I and trypsin-like serine and cysteine proteases, which may have unique specificities to achieve efficient breakdown of proteins in the peroxisomes. One mouse C57BL/6J strain-specific isocitrate dehydrogenase 1 isoform might be suitable to investigate potential phenotypes associated with the deficit of the intraperoxisomal reduced form of NADP (NADPH) and 2-oxoglutarate. Our biological knowledge discovery strategy enabled not only the identification of peroxisomal enzymes already described in the literature, but also the prediction of several novel proteins with possible roles in peroxisomal biochemistry and metabolism that are currently under experimental validation.

Atopic keratoconjunctivitis.

Atopic keratoconjunctivitis (AKC) represents a disease usually classified under the term of allergic conjunctivitis together with seasonal allergic conjunctivitis (SAC), perennial allergic conjunctivitis (PAC) and vernal keratoconjunctivitis (VKC). However, AKC and VKC have clinical and pathophysiological features quite different from SAC and PAC, in spite of some common markers of allergy. This article aims to review personal studies suggesting that allergic conjunctivitis (similarly to asthma, rhinitis and atopic dermatitis) is a heterogeneous disease entity with different preferential pathogenetic mechanisms and a spectrum of clinical expression which varies according to individual cases. AKC and VKC may thus represent a model of atopy quite distinct from the classical type-1 hypersensitivity mechanism.

EVIDENCE FOR RAISED K-CELL LEVELS IN TYPE-I DIABETES

The proportion of blood mononuclear cells forming low-affinity rosettes with sheep erythrocytes (K cells) was abnormally high in 13 (57%) of 23 children with classical type-1 diabetes at diagnosis but normal in children who had had diabetes for more than a year. A raised proportion of K cells was also found in 5 out of 10 unaffected siblings with islet-cell antibodies and at least one HLA haplotype in common with the diabetic proband; and in 10 (45%) of 22 subjects with type-1 diabetes and co-existent autoimmune thyroid disease irrespective of the duration of diabetes or the presence of islet-cell antibodies. These findings may be new evidence for lymphocyte-mediated β-cell destruction and support the idea of immuno-genetic heterogeneity within type-1 diabetes.